Data Analytics Graduate Credit Certificate Program

The Graduate Certificate in Data Analytics is a program for students who aim to pursue a career as a Data Analyst, Information Officer, or Quantitative Analyst and be responsible to presents data in visual and meaningful ways, create analytics solutions for business problems, use data to determine optimal solutions for business problems, provide technical leadership on data-related activities, and use quantitative methods to support business decisions.

Courses taken in the certificate program may be applied toward a master's degree in Data Analytics, subject to restrictions outlined in GCAC-309 Transfer Credit. Certificate students who wish to have certificate courses applied towards a graduate degree must apply and be admitted to that degree program. Admission to the graduate degree program is a separate step and is not guaranteed.​

Effective Semester: Spring 2024
Expiration Semester: Spring 2029

Admission Requirements

Applicants apply for admission to the program via the Graduate School application for admission. Requirements listed here are in addition to Graduate Council policies listed under GCAC-300 Admissions Policies. International applicants may be required to satisfy an English proficiency requirement; see GCAC-305 Admission Requirements for International Students for more information.

Applicants apply for admission to the program via the Graduate School application for admission. Requirements listed here are in addition to Graduate Council policies listed under GCAC-300 Admissions Policies. International applicants may be required to satisfy an English proficiency requirement; see GCAC-305 Admission Requirements for International Students for more information.

Applicants with undergraduate degrees in a quantitative discipline such as science, engineering, or business may apply. Students from other disciplines will be considered based on prior coursework. Applicants are generally expected to have a minimum combined junior/senior grade-point average of 3.0 (B) on a 4.0 scale.

Certificate Requirements

Requirements listed here are in addition to requirements listed in Graduate Council policy GCAC-212 Postbaccalaureate Credit Certificate Programs.

Requirements listed here are in addition to requirements listed in Graduate Council policy GCAC-212 Postbaccalaureate Credit Certificate Programs.

All courses must be completed with a minimum grade of C or better and an overall GPA of 3.0.

Courses

Graduate courses carry numbers from 500 to 699 and 800 to 899. Advanced undergraduate courses numbered between 400 and 499 may be used to meet some graduate degree requirements when taken by graduate students. Courses below the 400 level may not. A graduate student may register for or audit these courses in order to make up deficiencies or to fill in gaps in previous education but not to meet requirements for an advanced degree.

Learning Objectives

1. KNOW - Using analytical techniques, including end-to-end data analysis, descriptive and perspective analytics techniques, to extract information from data and to help people make better decisions.
2. APPLY/CREATE - To introduce the principles of network and predictive analytics for analyzing the interrelatedness of cyber-social and cyber-technical aspects of the society.
3. APPLY/CREATE - To introduce the principles, concepts, techniques and tools for visualizing information in large complex data sets.

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